Results (PhD Chapter 2)

This series of files compile all analyses done during Chapter 2:

All analyses have been done with R 3.6.0.

Click on the table of contents in the left margin to assess a specific analysis
Click on a figure to zoom it

To assess Section 2, click here.
To go back to the summary page, click here.

Human activities considered for the analyses:

Data is also available for the number of captured individuals for dogwhelk (Buccinum sp.), common crab (Cancer irroratus), snowcrab (Chinoecetes opilio), nordic shrimp (Pandalus borealis), arctic surfclam (Mactromeris polynyma) and american lobster (Homarus americanus) fisheries.

Workspace preparation

Here, we use data from subtidal ecosystems (see metadata files for more information)
Only stations that have been sampled both for abiotic parameters and benthic species were included.
The script below includes personnal functions, refined data, parameters for each campaign and global means, sd, se.

1. Maps

Depth

Isobaths

2. Modelling of non-fisheries human activities influence (WIP)

The influence of each human activity has been modelled at each station, in order to be later used in HMSC models.

We calculated a probability of influence for each activity \(P_{ij}\). For non-fisheries activities, the index \(I_{ij}\) has been calculated based on the distance from the source(s), bathymetry and hydrodynamics influences. We also included a weighting parameter specific for each activity, .

\[ P_{ij} = w_{j} . I_{ij} \]

\[ I_{ij} = f_{j} \left( \frac{D_{max, j} - D_{ij}}{D_{max, j}} \right) . \Delta Z_{ij} . H_{i} \]

  • \(i\) is a station
  • \(j\) is a human activity
  • \(w_{j}\) is the weighting parameter for activity \(j\)
  • \(f_{j}\) is the decay function of activity \(j\)
  • \(D_{ij}\) is the distance of station \(i\) from the source of activity \(j\)
  • \(\Delta Z_{ij}\) is the bathymetry index at station \(i\) for activity \(j\)
  • \(H_{i}\) is the hydrodynamic index at station \(i\)

STEP 1: Distance form the source and decay function

This corresponds to \(D_{ij}\) and \(f_{j}\) in Formula 2.

First, we need to calculate the distance of each station from the source(s) of the activity. This proxy will allow to take coasts and island into consideration (necessary at BSI), and will then be used to calculated the probabilities of influence. Distances are in meters and were computed with the package gdistance.

Second, each human activity has its own decay function \(f_{j}\). A careful literature review will be needed to support it, as parameters and mathematical links will be decided and settled by us. The help of Frédéric Guichard may be needed! A parameter max_inf needs to be defined for each activity, beyond which the effect of an AH can be neglected.

The following maps present the values of \(D_{ij}\) before and after the use of the decay function \(f_{j}\). The latter will be used for the following steps.

CityInf

Raw distances

With decay function

A linear decay function is used here, with parameter max_inf set to 4500.

InduInf

Raw distances

With decay function

A linear decay function is used here, with parameter max_inf set to 4500.

DredSit

Raw distances

With decay function

A linear decay function is used here, with parameter max_inf set to 1000.

MoorSit

Raw distances

With decay function

A linear decay function is used here, with parameter max_inf set to 3000.

RainSew

Raw distances

With decay function

A linear decay function is used here, with parameter max_inf set to 3000.

WastSew

Raw distances

With decay function

A linear decay function is used here, with parameter max_inf set to 3000.

CityWha

Raw distances

With decay function

A linear decay function is used here, with parameter max_inf set to 3000.

InduWha

Raw distances

With decay function

A linear decay function is used here, with parameter max_inf set to 3000.

STEP 2: Bathymetry index

This corresponds to \(\Delta Z_{ij}\) in Formula 2.

TO BE ADDED.

STEP 3: Hydrodynamic index

This corresponds to \(H_{i}\) in Formula 2.

TO BE ADDED.

STEP 4: Index of influence

This corresponds to \(I_{ij}\) in Formula 2.

Here, we will combine each component obtained in the previous steps to calculate \(I_{ij}\).

TO BE ADDED.

CityInf

InduInf

DredSit

MoorSit

RainSew

WastSew

CityWha

InduWha

STEP 5: Weighting parameter

This corresponds to \(w_{j}\) in Formula 1.

The following table shows the weights \(w_{j}\) for each human activity:

activity weights
CityInf 1
InduInf 1
DredSit 1
MoorSit 1
RainSew 1
WastSew 1
CityWha 1
InduWha 1
FishTrap 1
FishTraw 1
FishLine 1
FishNet 1
FishDred 1

STEP 6: Probability of influence

This corresponds to \(P_{ij}\) in Formula 1.

Finally, we combine \(I_{ij}\) and \(w_{j}\) in order to calculate \(P_{ij}\).

TO BE ADDED.

CityInf

InduInf

DredSit

MoorSit

RainSew

WastSew

CityWha

InduWha

Elliot Dreujou

2019-09-23